Ouput-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according to different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically-based model of a real case-study network as virtual reality.Peer ReviewedPostprint (author's final draft

Computational simulation of round thermal jets in an ambient cross flow using a large-scale hydrodynamic model

This paper presents the numerical simulation of single, circular, turbulent, thermal jets discharged into an ambient fluid body with a uniform cross flow. The study utilizes a 3D hydrodynamic model to predict the dynamics of the evolving jets, with the model simulations calibrated against benchmark laboratory experimental datasets. Within the numerical-experimental model comparisons, the mean centreline temperature and velocity fields of the evolving jets are investigated in order to understand and predict the jet diffusion characteristics within the flowing ambient fluid body. Direct comparison between the numerical model predictions and laboratory datasets reveals that, with appropriate parameterization of the mixing processes and the selection of an appropriate numerical grid resolution, the large-scale hydrodynamic model can simulate both the near- and farfield thermal jet behaviour with good overall agreement, thus revealing a valid modelling tool used by environmental regulators for assessing the conformity of water quality of marine wastewater discharges

SeagrassFinder: An Underwater Eelgrass Image Classification Dataset

This dataset is published as part of the publishing of the paper “SeagrassFinder: Deep Learning for Eelgrass Detection and Coverage Estimation in the Wild” in the Journal Ecological Informatics. The dataset is created as a machine learning dataset for training computer vision models to classify the presence of eelgrass. This dataset was created by the main author Jannik Elsäßer as part of his bachelor's thesis. The original video transect data in this dataset comes from DHI A/S work providing By og Havn a “Summer Status” report on the maritime environmental impacts of the Lynetteholm project. More information on the project and the report is available here: https://byoghavn.dk/mediebibliotek/lynetteholm-sommerstatus-2023/ The dataset consists of underwater images taken on a sled, dragged through the water by a survey vessel. The camera used is a Subsea HD-Camera made by LH-Camera. Images were created by taking 5 video frames each second, and then randomly sampling. Each image is labeled True or False for eelgrass presence. In total, the dataset consists of 8500 images from 6 different transects, with 4482 images containing eelgrass, and 4042 images not containing eelgrass. All images have been annotated by a both domain-experts, and non-domain experts. Images were annotated using a uniform sampling process. In the occurrence of any disagreement between annotators, images have been removed from the dataset. For more information on the dataset creation, please refer to the corresponding paper. We recommend using one transect as a test dataset, and not using a random split of all images to create the test dataset. When using a random split of all images, a form of data leakage occurs, since some images can be very similar to other images. An unfortunate limitation, we believe caused by the compression of the videos in the camera system, is some frames contain an echo or form of motion trail. This can lead to ghost like eelgrass features in some frames. This should be taken into consideration when applying the dataset in future locations

On the utilization of hydrological modelling for road drainage design under climate and land use change

Road drainage structures are often designed using methods that do not consider process-based representations of a landscape's hydrological response. This may create inadequately sized structures as coupled land cover and climate changes can lead to an amplified hydrological response. This study aims to quantify potential increases of runoff in response to future extreme rain events in a 61 km2 catchment (40% forested) in southwest Sweden using a physically-based hydrological modelling approach. We simulate peak discharge and water level (stage) at two types of pipe bridges and one culvert, both of which are commonly used at Swedish road/stream intersections, under combined forest clear-cutting and future climate scenarios for 2050 and 2100. The frequency of changes in peak flow and water level varies with time (seasonality) and storm size. These changes indicate that the magnitude of peak flow and the runoff response are highly correlated to season rather than storm size. In all scenarios considered, the dimensions of the current culvert are insufficient to handle the increase in water level estimated using a physically-based modelling approach. It also appears that the water level at the pipe bridges changes differently depending on the size and timing of the storm events. The findings of the present study and the approach put forward should be considered when planning investigations on and maintenance for areas at risk of high water flows. In addition, the research highlights the utility of physically-based hydrological models to identify the appropriateness of road drainage structure dimensioning.</p

Influence of hydrodynamic features in the transport and fate of hazard contaminants within touristic ports. Case study: Torre a Mare (Italy)

The environmental quality of Torre a Mare port (Italy) was assessed evaluating on one side, the chemical concentration of nine metals and metalloids within bottom sediments and on the other one, by exploring the impact of hydrodynamic conditions in contaminant’s transport within the most polluted basins. The investigated port was selected as case study because it resulted much more polluted than it was expected based on the touristic port activities and related stressors loading on it. In order to determine the origin and fate of contaminants in the port basin, 2D numerical simulations were carried out by MIKE21 software. The hydrodynamic module (HD) based on a rectangular grid was initially used to characterize the flow field into two domains that cover the inner and offshore harbor area. Then, advection–dispersion (AD) and water quality (WQ) modules were coupled in order to simulate the simultaneous processes of transport and dispersion of hypothetical pollutant sources. The dissolved/suspended sediment particulates (DSS) were selected as contaminant tracers. The comparative analysis between simulation responses and the real metal contaminant distribution showed high agreement, suggesting that contaminants mainly come from outside port and tend to accumulate in the inner basin. In fact, hydrodynamic circulations cause inflowing streams toward the harbor entrance and the particular port morphology hampers the exit of fine sediments from the inner basin, enhancing thus the accumulation of sediment-associated contaminants within the port area. The study confirms that the quality of touristic port areas strongly depends on both pollution sources located within and outside the port domain and it is controlled mainly by the hydrodynamic-driven processes